docstr: Compute metric. See :func:`compute` for more information.
  
  Args:
      *args: positional arguments passed to :func:`compute`
      **kwargs: keyword arguments passed to :func:`compute`
  
  Returns:
      dict[str, float]: dictionary with scalar values for evaluation
      dict[str, np.ndarray]: dictionary with arrays, e.g. for visualization of graphs
docstr_tok: ["Compute","metric",".","See",":","func",":","`","compute","`","for","more","information",".","Args",":","*","args",":","positional","arguments","passed","to",":","func",":","`","compute","`","*","*","kwargs",":","keyword","arguments","passed","to",":","func",":","`","compute","`","Returns",":","dict","[","str",",","float","]",":","dictionary","with","scalar","values","for","evaluation","dict","[","str",",","np.ndarray","]",":","dictionary","with","arrays",",","e.g",".","for","visualization","of","graphs"]
code: def __call__(
      self, *args: Any, **kwargs: Any
  ) -> tuple[dict[str, float], dict[str, np.ndarray] | None]:
      """
      Compute metric. See :func:`compute` for more information.
  
      Args:
          *args: positional arguments passed to :func:`compute`
          **kwargs: keyword arguments passed to :func:`compute`
  
      Returns:
          dict[str, float]: dictionary with scalar values for evaluation
          dict[str, np.ndarray]: dictionary with arrays, e.g. for visualization of graphs
      """
      return self.compute(*args, **kwargs)
  
file_path: MONAI/monai/apps/detection/metrics/coco.py
imports: from __future__ import annotations
  import logging
  import time
  from collections.abc import Sequence
  from typing import Any
  import numpy
label_desc: Use image node_id 2 for calling the COCOMetric obj's underlying member method code with example usage: obj.__call__() and returns: self